NanoMan: Self-Optimising Nanoscale Manufacturing Platforms for Achieving Multiscale Precision
NanoMan: Self-Optimising Nanoscale Manufacturing Platforms for Achieving Multiscale Precision
批准号:
EP/V055089/1
负责人:
Nicholas Warren
金额:
$182.5万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
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英文摘要
Improving our current lifestyle and ensuring health of a growing population is reliant on the development of more advanced consumer products. Many of these engineered products have advanced functionality delivered by particles with nanometre dimensions, many thousands of times smaller than the width of a human hair. The exact size of these nanoparticles determines the mechanism of action and performance for the specific application. In healthcare, many drugs require encapsulation within polymer nanoparticles for several reasons, including for dissolving insoluble drugs, protecting drugs from unwanted degradation (e.g. mRNA vaccines) and providing efficient delivery (anti-cancer drugs). In electronics, the colour and intensity of light produced can be finely tuned by controlling the size of quantum dot nanoparticles, thus resulting in much higher quality displays, ultra-thin smart coatings (e.g. for wearable technologies), advanced diagnostics, high intensity medical imaging or high efficiency solar panels. The accuracy required to produce these materials is phenomenal and often only achieved reproducibly in dedicated research laboratories by specialist scientists. There has therefore been little progress on scaling up in a cost-effective or sustainable manner. In this project we will build platform technologies, comprising advanced chemical reactors underpinned by computational intelligence, which can scale up production of advanced nanoparticle products without loss in the precise control over structural dimensions which are achieved in research laboratories. We will build laboratory reactors which can be programmed to monitor the nanoparticle formation process in real time and relate conditions to the particle properties. Throughout the manufacturing process the machine learning algorithms will direct the reactors towards achieving the desired specification through 'self-optimisation' of conditions. A critical part of the project is then using the data obtained in the lab experiments to build a relationship between process and product which can be transferred onto equipment which can make the materials on a commercially relevant scale in a process called augmented lossless scale-up. We will take the optimised laboratory nanoparticle formation processes and demonstrate scale in several manufacturing environments, including R&D process laboratories and Commercial manufacturing facilities at our partners sites. Such demonstration will encourage further innovation beyond the lifetime of the project which can work towards realising advanced materials currently confined to research laboratories.
期刊论文(7)
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DOI:
10.1109/cec53210.2023.10254023
发表时间:
2023-07
期刊:
2023 IEEE Congress on Evolutionary Computation (CEC)
影响因子:
--
作者:
[Jingyu Chen;John Oyekan]
通讯作者:
Jingyu Chen;John Oyekan
DOI:
10.1039/d2py00040g
发表时间:
2022-02-18
期刊:
POLYMER CHEMISTRY
影响因子:
4.6
作者:
[Knox, Stephen T., Parkinson, Sam J., Warren, Nicholas J.]
通讯作者:
Warren, Nicholas J.
DOI:
10.1021/acs.macromol.2c01798
发表时间:
2023-02-28
期刊:
Macromolecules
影响因子:
5.5
作者:
[Wilding CYP, Knox ST, Bourne RA, Warren NJ]
通讯作者:
Warren NJ
Continuous synthesis of block copolymer nanoparticles via telescoped RAFT solution and dispersion polymerisation in a miniature CSTR cascade
通过伸缩 RAFT 溶液和微型 CSTR 级联中的分散聚合连续合成嵌段共聚物纳米颗粒
DOI:
10.1039/d2re00475e
发表时间:
2023
期刊:
Reaction Chemistry & Engineering
影响因子:
3.9
作者:
[Pittaway P]
通讯作者:
Pittaway P
DOI:
10.1016/j.robot.2023.104489
发表时间:
2023-07
期刊:
Robotics Auton. Syst.
影响因子:
--
作者:
[Jingyu Chen;Ruidong Ma;J. Oyekan]
通讯作者:
Jingyu Chen;Ruidong Ma;J. Oyekan
Intelligent Continuous-flow Polymer Synthesis
-
批准号:EP/S000380/1
-
项目类别:Research Grant
-
资助金额:$38.96万
-
财政年份:2018
-
负责人:Nicholas Warren
-
依托单位:
国内基金
海外基金
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